Capstone and Reporting

Capstone and Reporting

Commands only. What each step does, why it is built this way, and the judgment behind it are in the book.

Infrastructure tier 8 labs ≈ 4.5–6 h Pure Python · no Docker Windows · macOS · Linux

Labs in this chapter

What you'll be able to do

  • Run the whole book end-to-end, chaining the four attribution engines into a single evidence graph for one operator.
  • Turn evidence into claims, each carrying a statement, a type, its provenance, and a falsifier.
  • Set a defensible confidence on every claim by a fixed rule rather than by feel, and state a low-confidence finding honestly as low.
  • Assemble a decision-ready report with a bottom line, findings traceable to source, a what-would-change section, and an attribution boundary.
  • Grade a report on coverage, provenance, calibration, and the overclaim count, watch a careless report mislead without stating a single false thing, and state where the whole method stops.
CHAPTER 15

Capstone and Reporting

The capstone chains every engine you have built over a single operator into an evidence graph, then produces a decision-ready report where each claim carries a statement, a source, a confidence, and the thing that would prove it wrong.

Written up in the book, commands and all.